Statistical physics of interacting neural networks

Wolfgang Kinzel, Richard Metzler and Ido Kanter

Physica A: Statistical Mechanics and its Applications, 2001, vol. 302, issue 1, 44-55

Abstract: Recent results on the statistical physics of time series generation and prediction are presented. A neural network is trained on quasi-periodic and chaotic sequences and overlaps to the sequence generator as well as the prediction errors are calculated numerically. For each network there exists a sequence for which it completely fails to make predictions. Two interacting networks show a transition to perfect synchronization. A pool of interacting networks shows good coordination in the minority game—a model of competition in a closed market. Finally, as a demonstration, a perceptron predicts bit sequences produced by human beings.

Date: 2001
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:302:y:2001:i:1:p:44-55

DOI: 10.1016/S0378-4371(01)00443-5

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